Journal of Food, Agriculture and Environment

Optimization of fermentation medium for β-fructofuranosidase production from Arthrobacter sp. 10138 using artificial neural network and genetic algorithms

Author(s):

Zheng Ruan ¹, Shiqiang Liu ¹, Zhang Cui ^{1, 2}, Dingding Su ^2*, Xiaosong Wu ⁴, Zhikai Dai ¹, Chengyao Luo¹, Chunlong Liao ¹, Yulong Yin ^{1, 3*}

Recieved Date: 2011-09-16, Accepted Date: 2012-01-10

Abstract:

In this paper, the optimization of medium components was reported for the production of β-fructofuranosidase (FFase) from Arthrobacter sp.10138. Experiments were conducted using the uniform design (UD), and the data were used to build an artificial neural network model. The concentrations of six medium components (sucrose, beef extract, yeast extract, (NH₄)₂HPO₄, KH₂PO₄ and MgSO₄ ) served as inputs to the neural network model, and the FFase activity served as outputs of the model. Using the genetic algorithms (GA), the input space of the neural network model was optimized to find out the optimum values for maximum FFase activity. Maximum FFase activity of 318.5U/mL was obtained at the GA-optimized concentrations of medium components (sucrose 33.0 g/L; beef extract 3.0 g/L; yeast extract 2.0 g/L; (NH₄)₂HPO₄ 4.0 g/L; KH₂PO₄ 0.5 g/L and MgSO₄·7H₂O 0.2 g/L). The FFase activity obtained by the ANN-GA was 15.6% higher than the maximum activity of FFase obtained by UD experiments.

Keywords:

β-fructofuranosidase, medium optimization, artificial neural network, genetic algorithms, uniform design method

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Journal: Journal of Food, Agriculture and Environment
Year: 2012
Volume: 10
Issue: 1
Category: Food and Health
Pages: 176-181

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